Multi-agent search for source localization in a turbulent medium

• We extend the gradient-less infotaxis search strategy to a distributed multi-agent system.
• Leveraging the spatio-temporal sensing capabilities of a team of mobile sensing agents speeds up the search process.
• The resulting information theoretic search strategy maximizes the information gained and improves the estimate of the source position.

We extend the gradient-less search strategy referred to as “infotaxis” to a distributed multi-agent system. “Infotaxis” is a search strategy that uses sporadic sensor measurements to determine the source location of materials dispersed in a turbulent medium. In this work, we leverage the spatio-temporal sensing capabilities of a mobile sensing agents to optimize the time spent finding and localizing the position of the source using a multi-agent collaborative search strategy. Our results suggest that the proposed multi-agent collaborative search strategy leverages the team's ability to obtain simultaneous measurements at different locations to speed up the search process. We present a multi-agent collaborative “infotaxis” strategy that uses the relative entropy of the system to synthesize a suitable search strategy for the team. The result is a collaborative information theoretic search strategy that results in control actions that maximize the information gained by the team, and improves estimates of the source position.